Evaluating Software Complexity Based on Decision Coverage

It is becoming increasingly difficult to ignore the complexity of software products. Software metrics are proposed to help show indications for quality, size, complexity, etc. of software products. In this paper, software metrics related to complexity are developed and evaluated. A dataset of many open source projects is built to assess the value of the developed metrics. Comparisons and correlations are conducted among the different tested projects. A classifica-tion is proposed to classify software code into different levels of complexity. The results showed that measuring the complexity of software products based on decision coverage gives a significant indicator of degree of complexity of those software products. However, such in-dicator is not exclusive as there are many other complexity indicators that can be measured in software products. In addition, we conducted a comparison among several available metric tools that can collect software complexity metrics. Results among those different tools were not consistent. Such comparison shows the need to have a unified standard for measuring and collecting complexity attributes.